Cargando…
Comparison of LSTM, Transformers, and MLP-mixer neural networks for gaze based human intention prediction
Collaborative robots have gained popularity in industries, providing flexibility and increased productivity for complex tasks. However, their ability to interact with humans and adapt to their behavior is still limited. Prediction of human movement intentions is one way to improve the robots adaptat...
Autores principales: | Pettersson, Julius, Falkman, Petter |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248176/ https://www.ncbi.nlm.nih.gov/pubmed/37304663 http://dx.doi.org/10.3389/fnbot.2023.1157957 |
Ejemplares similares
-
MLP-mmWP: High-Precision Millimeter Wave Positioning Based on MLP-Mixer Neural Networks
por: Zheng, Yadan, et al.
Publicado: (2023) -
Representation Learning Method for Circular Seal Based on Modified MLP-Mixer
por: Cao, Yuan, et al.
Publicado: (2023) -
MCR-ALS-based muscle synergy extraction method combined with LSTM neural network for motion intention detection
por: Zhao, Dazheng, et al.
Publicado: (2023) -
Prediction and comparison of postural discomfort based on MLP and quadratic regression
por: Lee, Jinwon, et al.
Publicado: (2021) -
GC-MLP: Graph Convolution MLP for Point Cloud Analysis
por: Wang, Yong, et al.
Publicado: (2022)